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qualifications involve: A PhD or equivalent degree in computer science, geospatial science, statistics, management science, information systems, environmental social sciences, political science, or other social
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statistical analysis. -Apply techniques for upscaling from experimental pilot-level data to relevant decision scopes and evaluate the quality and scientific validity of the resulting datasets and indicators
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archeology studies • Study of the human remains from these excavations and from collections already excavated. Job position requirements (skills/languages/required experience) • PhD- mandatory (will be
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characterizing primary cells of the immune system, experience with RNA quantification by RT-qPCR, familiarity with multicolor and spectral flow cytometry and cell sorting, and experience with statistical analysis
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or equivalent Skills/Qualifications We seek candidates with solid demonstrable experience in the application of statistical physics to neuroscience, and/or on the computational modelling of local and whole-brain
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, Psychology or any related field - hold a Doctorate degree/PhD in Cognitive Science, Neuroscience, Biomedicine, Psychology or any related field, with a focus on psycholinguistics & language learning in infancy
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responsible for developing models and conducting statistical analyses on data obtained from spectroscopic and geochemical analyses of geological and archaeological chert samples. Additionally, the applicant
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Experience4 - 10 Additional Information Eligibility criteria - PhD in computer science, data science, mathematics, applied mathematics, physics, statistics, biomedical informatics, computer vision, medical
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FieldEnvironmental science » Earth scienceEducation LevelPhD or equivalent Skills/Qualifications PhD in Oceanic Science, Physics, Mathematics or a related field at the time of appointment. Specific Requirements
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accredited. 1.- PhD degree in relevant agro-food/biotechnology 2.- Research experience in crop salinity studies, particularly in cereals and other herbaceous species: agronomical data, mineral content, stable